Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Analyst

MLabs
City of London
3 days ago
Create job alert
Junior Data Analyst (Product Focus)

Location: London, New York City (Office)

Compensation: $175K - $225K + Tokens/Equity

We are seeking a motivated Junior Data Analyst who is eager to learn, grow, and make a significant impact in a fast‑paced environment at the intersection of consumer technology and next‑generation finance. In this role, you will play a crucial part in supporting data initiatives across our product, helping various teams make informed decisions through clear analysis, reporting, and insight generation. You will work closely with senior data staff while gradually taking on more ownership as you develop your skills in a supportive, high‑autonomy environment. As a Junior Data Analyst, you will support critical data initiatives, translating raw data into actionable insights that directly influence product strategy and user experience. You will be instrumental in tracking key performance indicators (KPIs) and uncovering opportunities for growth and optimization.

Key Responsibilities
  • A/B Testing: Assist in the design, execution, and analysis of A/B tests to iteratively improve our consumer product experience and key conversion funnels
  • Metric Investigation: Investigate core product metrics to proactively uncover important trends, identify potential issues, and reveal growth opportunities
  • Reporting & Dashboards: Build, update, and maintain robust dashboards and visualizations to track team KPIs and present actionable insights to stakeholders
  • Data Extraction & Analysis: Write efficient SQL queries to extract and analyze data from our cloud‑based data warehouse
  • Analytical Support: Support the development of basic analytical frameworks or models to better understand user behavior and product adoption
  • Collaboration: Work closely with product management, engineering, and design teams to support their ongoing data and reporting needs
  • Communication: Present clear, concise, and compelling insights to stakeholders across the company, facilitating data‑driven decision‑making
  • Process Improvement: Contribute to the improvement of data processes, documentation, and best practices within the team
Requirements
  • Experience: 1–2+ years of experience in a data analyst, BI analyst, or related role (inclusive of relevant internships and project work)
  • Technical Skills: Solid SQL skills are a must (experience with BigQuery is a plus)
  • Programming: Familiarity with Python or R for data manipulation and statistical analysis
  • Visualization: Hands‑on experience building dashboards or data visualizations using tools like Looker, Grafana, Tableau, or similar platforms
  • Experimentation: Understanding of basic A/B testing concepts and experimentation frameworks
  • Analytical Ability: Proven ability to transform complex data into clear, actionable insights and recommendations
  • Soft Skills: Strong communication skills and a willingness to collaborate closely with cross‑functional teams
Preferred Qualifications
  • Experience working with consumer or product analytics data
  • Familiarity with event‑tracking platforms or user session analysis tools (e.g., FullStory)
  • Exposure to foundational statistical concepts (e.g., hypothesis testing, confidence intervals)
  • Experience with data pipelines or basic ETL tools
  • A genuine interest in blockchain, cryptocurrency, fintech, or fast‑growing consumer tech
  • Curiosity about machine learning concepts (no deep expertise required)
Benefits
  • Total Compensation: A highly competitive package, including a base salary plus tokens/equity, with total target compensation ranging from $175,000 to $225,000 USD, commensurate with experience
  • Flexibility: Flexible work arrangements to support work‑life balance
  • Health Coverage: Comprehensive health benefits package
  • Growth: Generous professional development budget to support continuous learning and skill growth
  • Culture: A collaborative, fast‑paced environment where your work is highly valued
  • Impact: Direct opportunity to contribute to the growth and success of our revolutionary consumer platform
Commitment to Equality and Accessibility

At MLabs, we are committed to offer equal opportunities to all candidates. We ensure no discrimination, accessible job adverts, and providing information in accessible formats. Our goal is to foster a diverse, inclusive workplace with equal opportunities for all. If you need any reasonable adjustments during any part of the hiring process or you would like to see the job‑advert in an accessible format please let us know at the earliest opportunity by emailing .


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.